Tối đa hóa Likelihood, Phần 1

# Compute sample mean and stdev, for use as model parameter value guesses
mu_guess = np.____(sample_distances)
sigma_guess = np.____(sample_distances)

# For each sample distance, compute the probability modeled by the parameter guesses
probs = np.zeros(len(sample_distances))
for n, distance in enumerate(sample_distances):
    probs[n] = gaussian_model(____, mu=____, sigma=____)

# Compute and print the log-likelihood as the sum() of the log() of the probabilities
loglikelihood = np.____(np.____(probs))
print('For guesses mu={:0.2f} and sigma={:0.2f}, the loglikelihood={:0.2f}'.format(mu_guess, sigma_guess, ____))